AIMC Topic: Machine Learning

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Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain-computer interfaces (BCIs): how to cope with individual differences so that better learning performance can be obtained for a new subject, ...

MLSeq: Machine learning interface for RNA-sequencing data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the last decade, RNA-sequencing technology has become method-of-choice and prefered to microarray technology for gene expression based classification and differential expression analysis since it produces less noisy data....

To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques.

Asian Pacific journal of cancer prevention : APJCP
Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are proposed for mining the hidden pattern in the dataset. Ensemble-I and Ensemble- II both are machine learni...

Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics.

Physics in medicine and biology
The use of treatment plan characteristics to predict patient-specific quality assurance (QA) measurement results has recently been reported as a strategy to help facilitate automated pre-treatment verification workflows or to provide a virtual assess...

Open access image repositories: high-quality data to enable machine learning research.

Clinical radiology
Originally motivated by the need for research reproducibility and data reuse, large-scale, open access information repositories have become key resources for training and testing of advanced machine learning applications in biomedical and clinical re...

A Novel Memory-Scheduling Strategy for Large Convolutional Neural Network on Memory-Limited Devices.

Computational intelligence and neuroscience
Recently, machine learning, especially deep learning, has been a core algorithm to be widely used in many fields such as natural language processing, speech recognition, object recognition, and so on. At the same time, another trend is that more and ...

Predicting the concentration of indoor culturable fungi using a kernel-based extreme learning machine (K-ELM).

International journal of environmental health research
Indoor fungal is of great significance for human health. The kernel-based extreme learning machine is employed to determine the most important parameters for predicting the concentration of indoor culturable fungi (ICF). For model training and statis...

An open access medical knowledge base for community driven diagnostic decision support system development.

BMC medical informatics and decision making
INTRODUCTION: While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will remain an important component ...